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You can't buy a hybrid cloud as a product nor as a service, and even if you could you would need to customise it for your unique requirements and constraints. The reality today is you need to buy the ingredients from a supplier then roll your own hybrid cloud and to manage this you need to put in place a Hybrid Cloud Manifesto.

The SPC-2 benchmark is a useful benchmark for bandwidth intensive sequential workloads, such as backup, ETL (extraction, translate, load) and large-scale analytics. Wikibon does a deep comparative analysis of the SPC-2 results, time-adjusting the pricing information to correct for different publication dates. Wikibon then analyses performance and price-performance together, and develops a guide to enable practitioners to understand the business options and best strategic fit. Wikibon concludes the Oracle ZS4-4 storage appliance dominates this high-bandwidth processing as of the best combination of good performance and great price performance at the high-end and mid-range of this market.

The thesis of the overall Wikibon research in this area is that within 2 years, the majority of IT installations will be moving to combine workloads together to share data using NAND flash as the only active storage media. This will save on IT budget and improve IT productivity, especially in the IT development function. Our research shows that these changes have the potential to reduce the typical IT budget by 34% over a five year period while delivering the same functionality to the business. The projected IT savings of moving to a shared-data all-flash datacenter for an organization with a $40M IT budget are $38M over 5 years, with an IRR of 246%, an annual ROI of 542%, and a breakeven of 13 months. Future research will look at the potential to maximize the contribution of IT to the business, and will conclude that IT budgets should increase to deliver historic improvements in internal productivity and increased business potential.

The Public Cloud market is still forming – but seems to be poised to soon enter the Early Majority stage of its development where user behavior, preferences, and strategies become more stable. Large enterprises are more discerning of Public Cloud IaaS offerings. Test and development appears to be a key entry point for them since scale, operational complexity, and security/compliance/regulatory demands require a more nuanced approach to Public Cloud for IaaS. Small and Medium enterprises have the greatest need for Public Cloud and should consider well-established, lower risk entry points to Public Cloud like SaaS, Email, and Web Applications before venturing into Mission Critical and IaaS workloads to help them navigate an increasingly complex and costly IT infrastructure environment.

Facebook’s Big Data Story: Where Behavior Meets Business

Every action you take on Facebook can metamorphose into a statistic; assigned and categorized according to behavior. And no matter what industry you’re in, Facebook’s behavioral data looks mighty juicy. We’re hungry for data’s insight into human nature, as illustrated in Pew’s recent study: theAmerican Life Project.

You could glean an image of social generosity just by looking through the report. Over the course of a month, some 40% of Facebook users sent out a friend request, while 63% received at least one. Personal messages follow a similar pattern, sending an average of 9 messages per month, but getting 12. And don’t get started on photo tagging. Thirty-five percent of Facebook users get tagged, but only do 12% of the tagging.

It seems a little backwards, to receive so much more than you give. But it’s not surprising, given you’re just one person to take all those actions, while multiple friends will collectively return more actions. That receiving action pool gets even bigger when you consider virtual connections beyond Friends. But there’s far more to understand about Facebook behavior than the first layer of the social graph.

Every major social outlet, online or off, provides a unique data set. But Facebook’s drawn a particular concourse for future potential. This is a prime target for emerging big data solutions, all contributing to the creation of Facebook’s a big data story. There’s a great deal Facebook wants to do with their data, serving up reports on ad returns, user demographics and relational results. An important platform leading the charge is Hadoop.

“If you look at Hadoop for as long as we have, you know it’s important–it’s a good choice,” says Pete O’Leary, VP of Customer Operations at Quantivo. “We get a lot of customers with a lot of data that have Facebook-like questions, but don’t have access to the resources. So they come to us.”

While Facebook juggles every facet of running a global network, an industry emerges from Facebook’s big data story, generating chapters all their own. Many fill in the gaps Facebook hasn’t gotten to yet. Focusing on the real-time aspects of relational data is a surge in behavioral analysis, understanding more about social interactions based on a given business’ needs.

Where behavioral analysis meets BI

Quantivo specializes in performance analysis solutions, with a hosted platform dedicated to the management of large volumes of data. It slims down the time you’re able to see the fruit of your labor and make changes accordingly. With a dearth of operational reports based on historical data, Quantivo’s also picked up on a trend that’s made its mark on BI. Tap past site performance, user purchases and responses for a deeper look at your specific user set. Quantivo lets you run public data sets against your own user data to better understand the customers you’ve got.

Not surprisingly, the Hadoop overlay in behavioral analysis is spawning a big data story as well. “It presents the best of both worlds,” O’Leary says. “Data coming from the world (not from your system) is in ways, beyond your control, but you can take that data and apply analytics to determine patterns. What are they saying about your brand?”

Quantivo is already seeing Hadoop proliferate through its own ecosystem, layering in MapReduce and other solutions to churn up the big data results they need. We know our needs for data will only continue to change. Now it’s a matter of building the flexibility to secure our fate.

There’s a number of companies cashing in on Facebook’s big data story. Friend2Friend rolled out a major update for its social metrics platform, while thismoment connects brands with end users.

Contributors: Saroj Kar

About Kristen Nicole

Named by Forbes as a top influencer in Big Data, Kristen Nicole is currently a Senior Editor at SiliconANGLE.com. She got her start with 606tech, a Chicago blog she dedicated to the social media space, going on to become the lead writer and Field Editor at Mashable.
Kristen Nicole has also contributed to other publications, from TIME Techland to Forbes. Her work has been syndicated across a number of media outlets, including The New York Times, and MSNBC.
Kristen Nicole published her first book, The Twitter Survival Guide, and is currently completing her second book on predictive analytics.
Follow my work (and some sprinklings of personal interests) on Google+